An Analysis of the Milwaukee Cryptosporidiosis Outbreak Based on a Dynamic Model of the Infection Process

Abstract

Although adverse reproductive outcomes have been associated with arsenic exposure, the extent and severity of the effects of chronic inhalation of low levels of arsenic on reproduction are not known. We conducted a hospital-based case-control study of stillbirths in a central Texas community that included a facility with more than a 60-year history of producing primarily arsenic-based agricultural products. We collected data on 119 cases and 267 controls randomly selected from healthy live-births at the same hospital and matched for year of birth. We abstracted medical and demographic data for the period January 1, 1983, to December 31, 1993, from hospital records and estimated socioeconomic status by median income from the 1990 Population and Housing Census data. We estimated arsenic exposure levels from airborne emission estimates and an atmospheric dispersion model and linked the results to a geographical information system (GIS) database. Exposure was linked by GIS to residential address at time of delivery. A conditional logistic regression model was fitted including maternal age, race/ethnicity, parity, income group, exposure as a categorical variable, and exposure-race/ethnicity interaction. The prevalence odds ratio observed for Hispanics in the high-exposure group (>100 ng per m3 arsenic) was 8.4, with a 95% confidence interval of 1.4-50.1.

Incorporating susceptible subpopulations in microbial risk assessment: pediatric exposures to enteroviruses in river water

“…Nevertheless, until recently, few researchers or risk assessors have employed an epidemiology-based disease transmission framework to characterize the risk to human health associated with waterborne pathogens (Cooper et al, 1986; EOA Inc., U.C. Berkeley, 1995Berkeley, , 1999Eisenberg et al, 1996Eisenberg et al, , 1998Soller et al, 2003a, b).…”

Disease transmission models for public health decision making: analysis of epidemic and endemic conditions caused by waterborne pathogens.

“…In some cases, this assumption is unrealistic. Relatively straightforward methods, however, modify the model structure so that the time spent in each state is other than exponential (10).…”

“…Surveillance data include nonoutbreak incidence levels of cryptosporidiosis, levels of oocysts in surface waters before and during the outbreak, and treatment efficiency both before and during the outbreak. We used an epidemiologically based mathematical model to integrate and analyze these data in the context of the Cryptosporidium outbreak (10).…”

“…The details of these methods and the following results are presented elsewhere (9,10). In this article, we briefly describe results in the context of health policy.…”

Seasonal Change in the Number of Cryptosporidium parvum Oocysts in Water Samples from the Rivers in Hokkaido, Japan, Detected by the Ferric Sulfate Flocculation Method.

“…Humans are infected with the pathogen through the fecal-oral route, namely by ingestion of contaminated food or water [2]. Water is perhaps the major source of massive outbreaks of the infection, so that the contamination of raw or treated water with the pathogen results in the outbreaks [3]. Despite the difficulties in detecting procedures, the number of the oocysts detected ranges from 0.005 to 252.7 oocysts/l of surface waters in different countries of the world [8,11].…”